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Research Assistant / Associate (Bioinformatics in Pathogen Genomics)

Job Description

A Research Assistant/Associate position is available in the Saw Swee Hock School of Public Health to support the Principal Investigator in research projects in the areas of bioinformatics and pathogen genomics. The Research Group focuses on the development and application of Bioinformatics algorithms and tools in the analysis of pathogen genomics for public health surveillance, particularly in the areas of tuberculosis and antimicrobial resistance.

The candidate will be working on the development and application of a data structure known as pan-genome graphs to represent the population structure of pathogen genomes for genomic surveillance and identification of clusters, which may indicate disease transmission. The candidate may also be tasked to work on ad-hoc activities in programming and/or data analysis for other research projects within the research group.

Duties and Responsibilities

The candidate is expected to contribute and assist the Principal Investigator in:

  • Literature review
  • Data collection and curation
  • Software development (Python and/or R)
  • Data analysis
  • Report(s) writing including presentations and manuscripts
  • Assistance in project administration

Requirements

  • Proficient in programming languages, especially Python (preferred) and R
  • Background in bioinformatics and/or graph theory is essential
  • Excellent written and oral communication skills
  • Good organization and administrative skills
  • Independent mature worker, able to work effectively with colleagues to achieve team goals
  • Knowledge of infectious disease is preferred but not essential

Qualifications

  • Bsc/Msc degree in a quantitative discipline (bioinformatics, computational biology, computer science, statistics, mathematics, data science) OR
  • Bsc/Msc degree in biological or life sciences with demonstrated quantitative skills/competence in programming and/or statistics.

Qualifications

  • Bsc/Msc degree in a quantitative discipline (bioinformatics, computational biology, computer science, statistics, mathematics, data science) OR
  • Bsc/Msc degree in biological or life sciences with demonstrated quantitative skills/competence in programming and/or statistics.

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